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What good are notebooks? Bridging the data science skills gap with collaboration (IBM Big Data & Analytics Hub)

By Juliet Sigmann posted Fri May 10, 2019 01:29 PM

  
This blog is posted on IBM Big Data & Analytics Hub here:
https://www.ibmbigdatahub.com/blog/bridging-data-science-skills-gap-collaboration
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What good are notebooks? Bridging the data science skills gap with collaboration

Portfolio Marketing Manager, IBM Data Science and AI, IBM

Predictive modeling and analytics have long been the domain of the data scientist and only the data scientist. But with modern tools, data science is becoming a team sport—business analysts and subject matter experts can join the analysis. While the players may have different skill sets and processes, in the world of predictive analytics, collaboration between them can position an entire team to win with data science.

Data scientists often are well-versed in open source tools, and they can code in open source languages. A business analyst is likely more comfortable with no-code, visual modeling. The key is enabling both roles to coexist and collaborate, leveraging each other’s unique knowledge sets to find the best answers to “what could happen?” and “what should we do?” And when that happens, the data science gap that many organizations—yours, perhaps—are experiencing can begin to close. Let’s see what can make that possible and how it works.

Modern predictive analytics brings business and data science together

For business analysts, today’s modern predictive analytics tools offer simpler, drag-and-drop data preparation, modeling and blending. This helps them derive insights and trends hidden in data and predict outcomes—even if they aren’t trained data scientists. A unified user experience can speed up analysis, tapping into complete algorithms and models that business analysts can use immediately. A data science- and AI-infused business strategy can help yield business outcomes like preventing customer churn, forecasting sales, uncovering fraud and more.

But what about data scientists? If analysis is easier to manage, where do they fit in this scenario? Does closing the skill gap mean rendering them obsolete? Not at all.

Modern tools can automate many of the more mundane data science tasks. This can free up data scientists to focus on areas where their impact is most powerful. Data scientists have specific, advanced expertise that allows them to harness the power of AI in ways uniquely tailored to specific business circumstances. For example, they could build custom AI models that zero on particular business questions or challenges.

In the case of IBM Watson Studio Desktop, the powerful open source capabilities used by data scientists are combined with the no-code, visual modeling of IBM SPSS Modeler not only to promote collaboration between scientists and analysts, but also to increase their productivity. And with that in mind, we just added a new feature to Watson Studio Desktop to make productivity gains even easier.

Drops of Jupyter: Introducing Notebooks

Watson Studio Desktop now includes Python3 Jupyter Notebooks that work seamlessly with its other desktop tools. Jupyter Notebooks are open-source web applications that make it possible to create and share documents with live code, equations, visualizations and narrative text. Data scientists use them for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning and much more.

With Python3 Jupyter Notebooks now included with Watson Studio Desktop, you can run small pieces of code that process your data and view the results of your computation. All data scientists have to do is add a Notebook to Watson Studio Desktop, write code, and share it with the business analyst who can provide feedback and notify your data science team when bias is detected or models need retraining. Business analysts and data scientists can work virtually or physically side-by-side, creating and analyzing predictive models.

Bridging the gap

The addition of Jupyter Notebooks to Watson Studio Desktop comes at a time when the demand for data scientists has never been greater, as reported by Indeed. There are more positions available than the current pool of data scientists can fill. The collaboration between data scientists and business analysts facilitated by Notebooks can increase productivity and efficiency so that the talent you have delivers the winning results you need. Business analysts and data scientists come together on the field and work as a team to deliver the insights needed to drive your business forward.

Begin a 30-day trial today

Ready to try Notebooks yourself? Check out Notebooks features by starting a no-cost, 30-day trial.

Not a Watson Studio Desktop user? Good news: all the above features are now also available in Watson Studio Cloud. These new features are coming soon for behind-the-firewall, site-wide deployment in Watson Studio Local.


>> READ on IBM Big Data & Analytics Hub:

https://www.ibmbigdatahub.com/blog/bridging-data-science-skills-gap-collaboration
#WatsonStudio
#Jupyter
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Fri May 17, 2019 04:19 AM

Jupyter have forum?